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# load data in 'global' chunk so it can be shared by all users of the dashboard library(biclust) data(BicatYeast) set.seed(1) res <- biclust(BicatYeast, method=BCPlaid(), verbose=FALSE)
selectInput("clusterNum", label = h3("Cluster number"), choices = list("1" = 1, "2" = 2, "3" = 3, "4" = 4, "5" = 5), selected = 1)
Microarray data matrix for 80 experiments with Saccharomyces Cerevisiae
organism extracted from R's biclust
package.
Sebastian Kaiser, Rodrigo Santamaria, Tatsiana Khamiakova, Martin Sill, Roberto Theron, Luis Quintales, Friedrich Leisch and Ewoud De Troyer. (2015). biclust: BiCluster Algorithms. R package version 1.2.0. http://CRAN.R-project.org/package=biclust
num <- reactive(as.integer(input$clusterNum)) col = colorRampPalette(c("red", "white", "darkblue"), space="Lab")(10) renderPlot({ p = par(mai=c(0,0,0,0)) heatmapBC(BicatYeast, res, number=num(), xlab="", ylab="", order=TRUE, useRaster=TRUE, col=col) par(p) })
renderPlot( parallelCoordinates(BicatYeast, res, number=num()) )
# only display table for values in cluster 4 renderTable( BicatYeast[which(res@RowxNumber[, num()]), which(res@NumberxCol[num(), ])] )
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